Syllabus
Registration via LPIS
Pre-course assignment:
Read Chapter 1-6 of Emma Bell, Bill Harley, and Alan Bryman: Business Research Methods, 6th edition, Oxford University Press, 2022, ISBN: 9780198869443. https://global.oup.com/ukhe/product/business-research-methods-9780198869443?cc=at&lang=en&
We expect you to be familiar with the core concepts from these chapters (quiz in the first unit).
Part 1:
Input lectures and discussion
- What is research?
- Scientific analysis in a Master thesis
- What is a research question and how to find one for your Master thesis?
- Research idea generation
- Major steps to write a Master thesis
Methods and data: Elaborate the main methods used in empirical research, develop a master thesis proposal that uses that method (assignment 1, group presentations)
Part 3:
Assignment 2: Learn from examples: Choose a paper and reflect on it, develop a master thesis proposal that builds on this paper (individual assignment)
Students are introduced to core ideas of scientific research. After finishing the course, students should be able to
- understand the concept of a research question and how and why different research designs are used to answer certain research questions;
- understand and can apply the main steps needed for drafting a research project;
- can identify major steps in assessing a scientific paper;
- can develop a master thesis topic and a research proposal based on prior research.
Input presentations by instructors, individual assignments, group work.
Compulsory attendance for input lectures (part 1), for group presentations (part 2) and individual presentations (part 3). One to one consultations for the individual assignment (part 3) will be individually scheduled with the lecturers.
Pre-course-assignment/multiple-choice quiz: 10% Online on October 5, 2026.
Group Assignment “Part 2”: 30%
Individual Assignment “Part 3”: 60%
For this course, only one of two grades (pass/fail) will be awarded.
A "pass" grade requires a minimum score of 50% for each assignment and 75% in total.
Usage of AI-Tools:
The responsible use of AI tools is encouraged. Students may leverage AI to support their individual academic learning and development needs, which include but are not limited to text summarization, data analytics, and language/grammar correction. However, it is imperative to maintain a transparent record of their use and to reflect critically on the output. Students should take responsibility for carefully evaluating the results produced by AI tools. While these tools offer valuable assistance, they must be applied thoughtfully to ensure alignment with core objectives and scientific rigor. Students take full responsibility for any output generated by AI.
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